Wan POV Doggy Style (i2v)
doggyPOV_v1_1.safetensors LORA / Wan Video 14B i2v 480p
- Model Name
- Wan POV Doggy Style (i2v)
- Version
- v1.1
- Creator
- lazerblazer
- Size
- 513.87 MB
- Downloads
- 24,748
- Trigger
- POVdog A POV video showing a man having sex doggy style sex with a woman.
- BTIH
- AAD7630A85D1F2BC967E6C99FC364D2DFA9377F5
- BTMH
- 08DFF0CD26615470F37B264987D2CA8C4C76B8C1DEC01D32E075E49CA257DFE4
- SHA256
- 4DDABAB30906EAAFFD5260B44D0B8E6E079093FEC156A758C532433754BF5119
- Upload Date
- about a year ago
- Uploader
- CivitasBay.org
- Status
- 7 Seeders0 Peers
Trained for image2video generation, not tested on text2vid
v1.1 UPDATE
Version 1.1 is a significant improvement of v1.0. It produces the doggy style motion consistently. The LoRA was trained on vertical videos - it has been reported that wide aspect videos may have some issues. Please leave some feedback if you have issues with it.
Note: I noticed there can be some image artifacts that appear, usually on the ass. I think this is due to low resolution videos in my data set. I looked into improving the quality with AI upscaling, but ran into a lot off issues that ended up making the videos worse, so this will do for now.
Trigger word is POVdog. "A POV video showing a man having sex doggy style sex with a woman." and "Ass movement and bounce is emphasized" can help too.
I used aipinups69's https://civarchive.com/models/1358184/wan-21-penis-cock-dick-lora-t2v-i2v?modelVersionId=1534254 at strength 0.5 in my testing again and it worked great.
v1 -
This is my first attempt at training anything and is still a work in progress. It seems to work okay - some feedback on how to improve is always appreciated. I trained on 480p 14B, I am not sure if it works for the 720p version or not.
Trigger word is: POVdog. The phrase "A POV video showing man having sex doggy style sex with a woman." Was included in most of the training data as well.
In my testing I found this works better with aipinups69's https://civarchive.com/models/1358184/wan-21-penis-cock-dick-lora-t2v-i2v?modelVersionId=1534254 at low strength (0.4 - 0.5) to keep the man bits not looking too deformed.
I need to take a closer look to my training process and data set and will hopefully improve this in the week. Training took about 10 hours on two 4090s which seems a lot longer than other people have trained their models, so I definitely have some inefficiencies.
Let me know what y'all think!
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